Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/156411
Title: Model-free predictive current control of SPMSM drives using extended state observer
Authors: Yuan, Xin
Zuo, Yuefei
Fan, Ying
Lee, Christopher Ho Tin
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Source: Yuan, X., Zuo, Y., Fan, Y. & Lee, C. H. T. (2021). Model-free predictive current control of SPMSM drives using extended state observer. IEEE Transactions On Industrial Electronics, 69(7), 6540-6550. https://dx.doi.org/10.1109/TIE.2021.3095816
Project: NRF-NRFF12- 2020-0003
Journal: IEEE Transactions on Industrial Electronics
Abstract: Conventional predictive control (PC) has been employed for machine drives due to good dynamic response and easy implementation. However, the disturbance caused by machine parameter mismatch is one of main barriers to its widespread application. In order to deal with this issue, this work proposes a novel model-free predictive current control (MFPCC) for surfaced permanent magnet synchronous machines (SPMSM). The contribution of this work is that a novel extended state observer (ESO) is proposed and the proposed MFPCC only utilizes the input and output knowledge of the plant without using any machine parameter in controller, which can effectively suppress the disturbances. In addition, the effect of the initial machine inductance parameter mismatch on the conventional ESO of MFPCC is analyzed in detail. The proposed MFPCC is validated and compared against three methods, namely PC without ESO, PC using ESO, and MFPCC using ESO. The experimental results have been carried out to verify the effectiveness of the proposed MFPCC.
URI: https://hdl.handle.net/10356/156411
ISSN: 0278-0046
DOI: 10.1109/TIE.2021.3095816
Rights: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TIE.2021.3095816.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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